We have identified 11 major topics in Bioinformatics. Within each topic we used up to 3 search terms in 6 databases of scientific articles.
The data is limited to the establishment of PLoS in 2003
p <- ordered_df %>%
ggplot(aes(ordering, group = topic))+
geom_tile(aes(y = cum_total/2,
height = cum_total,
width = 0.9,
fill = topic)) +
geom_text(aes(y = cum_total, label = topic), hjust = "left", fontface = "bold", nudge_y = 50) +
scale_fill_viridis_d() +
coord_cartesian(clip = "off", expand = FALSE) +
coord_flip() +
#animate
transition_states(Year, transition_length = 8, state_length = 4, wrap = FALSE) +
ease_aes("cubic-in-out") +
#aesthetics
labs(subtitle = "Trends in sequening methods",title = "Year {closest_state}", y = "cumulative total papers") +
theme(plot.background = element_blank(),
legend.position = "none",
axis.ticks.y = element_blank(),
axis.text.y = element_blank(),
text = element_text(size=14),
plot.title = element_text(size = 35)) +
ylim(0,1300) +
xlab("")
#rendering the animation
animate(p, nframes = 750,
fps = 20,
end_pause = 10)